Overview

Dataset statistics

Number of variables26
Number of observations400
Missing cells1009
Missing cells (%)9.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory81.4 KiB
Average record size in memory208.3 B

Variable types

Numeric12
Boolean3
Categorical11

Variable descriptions

filesFiles in the filesystem
datecCreation date
datemModification date

Alerts

wc has a high cardinality: 92 distinct values High cardinality
id is highly correlated with sg and 3 other fieldsHigh correlation
sg is highly correlated with id and 3 other fieldsHigh correlation
al is highly correlated with id and 4 other fieldsHigh correlation
su is highly correlated with bgrHigh correlation
bgr is highly correlated with suHigh correlation
bu is highly correlated with sc and 1 other fieldsHigh correlation
sc is highly correlated with id and 4 other fieldsHigh correlation
sod is highly correlated with al and 1 other fieldsHigh correlation
hemo is highly correlated with id and 5 other fieldsHigh correlation
id is highly correlated with sg and 2 other fieldsHigh correlation
sg is highly correlated with id and 1 other fieldsHigh correlation
al is highly correlated with id and 1 other fieldsHigh correlation
su is highly correlated with bgrHigh correlation
bgr is highly correlated with suHigh correlation
bu is highly correlated with sc and 1 other fieldsHigh correlation
sc is highly correlated with bu and 1 other fieldsHigh correlation
sod is highly correlated with scHigh correlation
hemo is highly correlated with id and 3 other fieldsHigh correlation
al is highly correlated with sc and 1 other fieldsHigh correlation
bu is highly correlated with scHigh correlation
sc is highly correlated with al and 2 other fieldsHigh correlation
hemo is highly correlated with al and 1 other fieldsHigh correlation
pc is highly correlated with rc and 2 other fieldsHigh correlation
htn is highly correlated with rc and 3 other fieldsHigh correlation
rbc is highly correlated with pcv and 1 other fieldsHigh correlation
rc is highly correlated with pc and 3 other fieldsHigh correlation
pcc is highly correlated with pcHigh correlation
pcv is highly correlated with pc and 4 other fieldsHigh correlation
dm is highly correlated with htnHigh correlation
classification is highly correlated with htn and 3 other fieldsHigh correlation
ane is highly correlated with rc and 1 other fieldsHigh correlation
id is highly correlated with sg and 11 other fieldsHigh correlation
age is highly correlated with htnHigh correlation
bp is highly correlated with pcv and 1 other fieldsHigh correlation
sg is highly correlated with id and 5 other fieldsHigh correlation
al is highly correlated with id and 14 other fieldsHigh correlation
su is highly correlated with bgr and 6 other fieldsHigh correlation
rbc is highly correlated with id and 6 other fieldsHigh correlation
pc is highly correlated with id and 10 other fieldsHigh correlation
pcc is highly correlated with al and 1 other fieldsHigh correlation
ba is highly correlated with al and 1 other fieldsHigh correlation
bgr is highly correlated with al and 6 other fieldsHigh correlation
bu is highly correlated with al and 9 other fieldsHigh correlation
sc is highly correlated with bu and 6 other fieldsHigh correlation
sod is highly correlated with pc and 6 other fieldsHigh correlation
pot is highly correlated with bu and 3 other fieldsHigh correlation
hemo is highly correlated with id and 15 other fieldsHigh correlation
pcv is highly correlated with id and 19 other fieldsHigh correlation
wc is highly correlated with id and 12 other fieldsHigh correlation
rc is highly correlated with id and 21 other fieldsHigh correlation
htn is highly correlated with id and 12 other fieldsHigh correlation
dm is highly correlated with id and 5 other fieldsHigh correlation
cad is highly correlated with su and 1 other fieldsHigh correlation
appet is highly correlated with id and 6 other fieldsHigh correlation
pe is highly correlated with al and 6 other fieldsHigh correlation
ane is highly correlated with bu and 4 other fieldsHigh correlation
classification is highly correlated with id and 6 other fieldsHigh correlation
age has 9 (2.2%) missing values Missing
al has 46 (11.5%) missing values Missing
bgr has 44 (11.0%) missing values Missing
bp has 12 (3.0%) missing values Missing
bu has 19 (4.8%) missing values Missing
hemo has 52 (13.0%) missing values Missing
pc has 65 (16.2%) missing values Missing
pcv has 70 (17.5%) missing values Missing
pot has 88 (22.0%) missing values Missing
rbc has 152 (38.0%) missing values Missing
rc has 130 (32.5%) missing values Missing
sc has 17 (4.2%) missing values Missing
sg has 47 (11.8%) missing values Missing
sod has 87 (21.8%) missing values Missing
su has 49 (12.2%) missing values Missing
wc has 105 (26.2%) missing values Missing
id is uniformly distributed Uniform
id has unique values Unique
al has 199 (49.8%) zeros Zeros
su has 290 (72.5%) zeros Zeros

Reproduction

Analysis started2022-04-11 06:39:28.659177
Analysis finished2022-04-11 08:09:57.939040
Duration1 hour, 30 minutes and 29.28 seconds
Software versionpandas-profiling v3.1.0
Download configurationconfig.json

Variables

age
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct76
Distinct (%)19.4%
Missing9
Missing (%)2.2%
Infinite0
Infinite (%)0.0%
Mean51.48337596
Minimum2
Maximum90
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2022-04-11T13:41:37.355531image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile19
Q142
median55
Q364.5
95-th percentile74.5
Maximum90
Range88
Interquartile range (IQR)22.5

Descriptive statistics

Standard deviation17.16971409
Coefficient of variation (CV)0.3335001594
Kurtosis0.0578404946
Mean51.48337596
Median Absolute Deviation (MAD)10
Skewness-0.6682594692
Sum20130
Variance294.7990819
MonotonicityNot monotonic
2022-04-11T13:41:37.485709image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6019
 
4.8%
6517
 
4.2%
4812
 
3.0%
5012
 
3.0%
5512
 
3.0%
4711
 
2.8%
5610
 
2.5%
5910
 
2.5%
4510
 
2.5%
5410
 
2.5%
Other values (66)268
67.0%
ValueCountFrequency (%)
21
 
0.2%
31
 
0.2%
41
 
0.2%
52
0.5%
61
 
0.2%
71
 
0.2%
83
0.8%
111
 
0.2%
122
0.5%
141
 
0.2%
ValueCountFrequency (%)
901
 
0.2%
831
 
0.2%
821
 
0.2%
811
 
0.2%
804
1.0%
791
 
0.2%
781
 
0.2%
765
1.2%
755
1.2%
743
0.8%

al
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
ZEROS

Distinct6
Distinct (%)1.7%
Missing46
Missing (%)11.5%
Infinite0
Infinite (%)0.0%
Mean1.016949153
Minimum0
Maximum5
Zeros199
Zeros (%)49.8%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2022-04-11T13:41:37.578489image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile4
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.352678913
Coefficient of variation (CV)1.330134264
Kurtosis-0.3833766021
Mean1.016949153
Median Absolute Deviation (MAD)0
Skewness0.9981572421
Sum360
Variance1.829740241
MonotonicityNot monotonic
2022-04-11T13:41:37.775847image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0199
49.8%
144
 
11.0%
243
 
10.8%
343
 
10.8%
424
 
6.0%
51
 
0.2%
(Missing)46
 
11.5%
ValueCountFrequency (%)
0199
49.8%
144
 
11.0%
243
 
10.8%
343
 
10.8%
424
 
6.0%
51
 
0.2%
ValueCountFrequency (%)
51
 
0.2%
424
 
6.0%
343
 
10.8%
243
 
10.8%
144
 
11.0%
0199
49.8%

ane
Boolean

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)0.5%
Missing1
Missing (%)0.2%
Memory size928.0 B
False
339 
True
60 
(Missing)
 
1
ValueCountFrequency (%)
False339
84.8%
True60
 
15.0%
(Missing)1
 
0.2%
2022-04-11T13:41:37.857583image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

appet
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)0.5%
Missing1
Missing (%)0.2%
Memory size3.2 KiB
good
317 
poor
82 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowgood
2nd rowgood
3rd rowpoor
4th rowpoor
5th rowgood

Common Values

ValueCountFrequency (%)
good317
79.2%
poor82
 
20.5%
(Missing)1
 
0.2%

Length

2022-04-11T13:41:37.927883image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-04-11T13:41:37.994150image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

ba
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)0.5%
Missing4
Missing (%)1.0%
Memory size3.2 KiB
notpresent
374 
present
 
22

Length

Max length10
Median length10
Mean length9.833333333
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rownotpresent
2nd rownotpresent
3rd rownotpresent
4th rownotpresent
5th rownotpresent

Common Values

ValueCountFrequency (%)
notpresent374
93.5%
present22
 
5.5%
(Missing)4
 
1.0%

Length

2022-04-11T13:41:38.055153image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-04-11T13:41:38.124950image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

bgr
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct146
Distinct (%)41.0%
Missing44
Missing (%)11.0%
Infinite0
Infinite (%)0.0%
Mean148.0365169
Minimum22
Maximum490
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2022-04-11T13:41:38.212001image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile78.75
Q199
median121
Q3163
95-th percentile307.25
Maximum490
Range468
Interquartile range (IQR)64

Descriptive statistics

Standard deviation79.28171424
Coefficient of variation (CV)0.5355551179
Kurtosis4.225593588
Mean148.0365169
Median Absolute Deviation (MAD)25
Skewness2.010773173
Sum52701
Variance6285.590212
MonotonicityNot monotonic
2022-04-11T13:41:38.346197image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9910
 
2.5%
939
 
2.2%
1009
 
2.2%
1078
 
2.0%
1316
 
1.5%
1406
 
1.5%
1096
 
1.5%
926
 
1.5%
1176
 
1.5%
1306
 
1.5%
Other values (136)284
71.0%
(Missing)44
 
11.0%
ValueCountFrequency (%)
221
 
0.2%
705
1.2%
743
0.8%
752
 
0.5%
764
1.0%
783
0.8%
793
0.8%
802
 
0.5%
813
0.8%
823
0.8%
ValueCountFrequency (%)
4902
0.5%
4631
0.2%
4471
0.2%
4251
0.2%
4242
0.5%
4231
0.2%
4151
0.2%
4101
0.2%
3801
0.2%
3602
0.5%

bp
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct10
Distinct (%)2.6%
Missing12
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean76.46907216
Minimum50
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2022-04-11T13:41:38.453660image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum50
5-th percentile60
Q170
median80
Q380
95-th percentile100
Maximum180
Range130
Interquartile range (IQR)10

Descriptive statistics

Standard deviation13.68363749
Coefficient of variation (CV)0.1789434226
Kurtosis8.646095189
Mean76.46907216
Median Absolute Deviation (MAD)10
Skewness1.605428957
Sum29670
Variance187.2419351
MonotonicityNot monotonic
2022-04-11T13:41:38.546565image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
80116
29.0%
70112
28.0%
6071
17.8%
9053
13.2%
10025
 
6.2%
505
 
1.2%
1103
 
0.8%
1401
 
0.2%
1801
 
0.2%
1201
 
0.2%
(Missing)12
 
3.0%
ValueCountFrequency (%)
505
 
1.2%
6071
17.8%
70112
28.0%
80116
29.0%
9053
13.2%
10025
 
6.2%
1103
 
0.8%
1201
 
0.2%
1401
 
0.2%
1801
 
0.2%
ValueCountFrequency (%)
1801
 
0.2%
1401
 
0.2%
1201
 
0.2%
1103
 
0.8%
10025
 
6.2%
9053
13.2%
80116
29.0%
70112
28.0%
6071
17.8%
505
 
1.2%

bu
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct118
Distinct (%)31.0%
Missing19
Missing (%)4.8%
Infinite0
Infinite (%)0.0%
Mean57.42572178
Minimum1.5
Maximum391
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2022-04-11T13:41:38.687252image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum1.5
5-th percentile17
Q127
median42
Q366
95-th percentile162
Maximum391
Range389.5
Interquartile range (IQR)39

Descriptive statistics

Standard deviation50.50300585
Coefficient of variation (CV)0.8794492133
Kurtosis9.345288576
Mean57.42572178
Median Absolute Deviation (MAD)16
Skewness2.634374459
Sum21879.2
Variance2550.5536
MonotonicityNot monotonic
2022-04-11T13:41:38.825855image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4615
 
3.8%
2513
 
3.2%
1911
 
2.8%
4010
 
2.5%
159
 
2.2%
489
 
2.2%
509
 
2.2%
189
 
2.2%
328
 
2.0%
498
 
2.0%
Other values (108)280
70.0%
(Missing)19
 
4.8%
ValueCountFrequency (%)
1.51
 
0.2%
102
 
0.5%
159
2.2%
167
1.8%
177
1.8%
189
2.2%
1911
2.8%
207
1.8%
211
 
0.2%
226
1.5%
ValueCountFrequency (%)
3911
0.2%
3221
0.2%
3091
0.2%
2411
0.2%
2351
0.2%
2231
0.2%
2191
0.2%
2171
0.2%
2151
0.2%
2081
0.2%

cad
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)0.8%
Missing2
Missing (%)0.5%
Memory size3.2 KiB
no
362 
yes
 
34
no
 
2

Length

Max length3
Median length2
Mean length2.090452261
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowno
2nd rowno
3rd rowno
4th rowno
5th rowno

Common Values

ValueCountFrequency (%)
no362
90.5%
yes34
 
8.5%
no2
 
0.5%
(Missing)2
 
0.5%

Length

2022-04-11T13:41:38.942074image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-04-11T13:41:39.017280image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

classification
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
ckd
248 
notckd
150 
ckd
 
2

Length

Max length6
Median length3
Mean length4.13
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowckd
2nd rowckd
3rd rowckd
4th rowckd
5th rowckd

Common Values

ValueCountFrequency (%)
ckd248
62.0%
notckd150
37.5%
ckd 2
 
0.5%

Length

2022-04-11T13:41:39.182941image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-04-11T13:41:39.243914image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

dm
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct5
Distinct (%)1.3%
Missing2
Missing (%)0.5%
Memory size3.2 KiB
no
258 
yes
134 
no
 
3
yes
 
2
yes
 
1

Length

Max length4
Median length2
Mean length2.359296482
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st rowyes
2nd rowno
3rd rowyes
4th rowno
5th rowno

Common Values

ValueCountFrequency (%)
no258
64.5%
yes134
33.5%
no3
 
0.8%
yes2
 
0.5%
yes1
 
0.2%
(Missing)2
 
0.5%

Length

2022-04-11T13:41:39.313600image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-04-11T13:41:39.388251image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

hemo
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct115
Distinct (%)33.0%
Missing52
Missing (%)13.0%
Infinite0
Infinite (%)0.0%
Mean12.52643678
Minimum3.1
Maximum17.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2022-04-11T13:41:39.471658image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum3.1
5-th percentile7.9
Q110.3
median12.65
Q315
95-th percentile16.9
Maximum17.8
Range14.7
Interquartile range (IQR)4.7

Descriptive statistics

Standard deviation2.912586609
Coefficient of variation (CV)0.2325151725
Kurtosis-0.4713980437
Mean12.52643678
Median Absolute Deviation (MAD)2.35
Skewness-0.3350946792
Sum4359.2
Variance8.483160754
MonotonicityNot monotonic
2022-04-11T13:41:39.593947image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1516
 
4.0%
10.98
 
2.0%
13.67
 
1.8%
137
 
1.8%
9.87
 
1.8%
11.17
 
1.8%
10.36
 
1.5%
11.36
 
1.5%
13.96
 
1.5%
126
 
1.5%
Other values (105)272
68.0%
(Missing)52
 
13.0%
ValueCountFrequency (%)
3.11
0.2%
4.81
0.2%
5.51
0.2%
5.61
0.2%
5.81
0.2%
62
0.5%
6.11
0.2%
6.21
0.2%
6.31
0.2%
6.61
0.2%
ValueCountFrequency (%)
17.83
0.8%
17.71
 
0.2%
17.61
 
0.2%
17.51
 
0.2%
17.42
0.5%
17.31
 
0.2%
17.22
0.5%
17.12
0.5%
174
1.0%
16.92
0.5%

htn
Boolean

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)0.5%
Missing2
Missing (%)0.5%
Memory size928.0 B
False
251 
True
147 
(Missing)
 
2
ValueCountFrequency (%)
False251
62.7%
True147
36.8%
(Missing)2
 
0.5%
2022-04-11T13:41:39.677646image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct400
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean199.5
Minimum0
Maximum399
Zeros1
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2022-04-11T13:41:39.763280image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile19.95
Q199.75
median199.5
Q3299.25
95-th percentile379.05
Maximum399
Range399
Interquartile range (IQR)199.5

Descriptive statistics

Standard deviation115.6143013
Coefficient of variation (CV)0.5795203073
Kurtosis-1.2
Mean199.5
Median Absolute Deviation (MAD)100
Skewness0
Sum79800
Variance13366.66667
MonotonicityStrictly increasing
2022-04-11T13:41:39.878755image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
01
 
0.2%
2631
 
0.2%
2731
 
0.2%
2721
 
0.2%
2711
 
0.2%
2701
 
0.2%
2691
 
0.2%
2681
 
0.2%
2671
 
0.2%
2661
 
0.2%
Other values (390)390
97.5%
ValueCountFrequency (%)
01
0.2%
11
0.2%
21
0.2%
31
0.2%
41
0.2%
51
0.2%
61
0.2%
71
0.2%
81
0.2%
91
0.2%
ValueCountFrequency (%)
3991
0.2%
3981
0.2%
3971
0.2%
3961
0.2%
3951
0.2%
3941
0.2%
3931
0.2%
3921
0.2%
3911
0.2%
3901
0.2%

pc
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct2
Distinct (%)0.6%
Missing65
Missing (%)16.2%
Memory size3.2 KiB
normal
259 
abnormal
76 

Length

Max length8
Median length6
Mean length6.453731343
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rownormal
2nd rownormal
3rd rownormal
4th rowabnormal
5th rownormal

Common Values

ValueCountFrequency (%)
normal259
64.8%
abnormal76
 
19.0%
(Missing)65
 
16.2%

Length

2022-04-11T13:41:40.015225image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-04-11T13:41:40.091549image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

pcc
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)0.5%
Missing4
Missing (%)1.0%
Memory size3.2 KiB
notpresent
354 
present
42 

Length

Max length10
Median length10
Mean length9.681818182
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rownotpresent
2nd rownotpresent
3rd rownotpresent
4th rowpresent
5th rownotpresent

Common Values

ValueCountFrequency (%)
notpresent354
88.5%
present42
 
10.5%
(Missing)4
 
1.0%

Length

2022-04-11T13:41:40.157407image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-04-11T13:41:40.213050image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

pcv
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct44
Distinct (%)13.3%
Missing70
Missing (%)17.5%
Memory size3.2 KiB
52
 
21
41
 
21
48
 
19
44
 
19
40
 
16
Other values (39)
234 

Length

Max length3
Median length2
Mean length2
Min length1

Unique

Unique10 ?
Unique (%)3.0%

Sample

1st row44
2nd row38
3rd row31
4th row32
5th row35

Common Values

ValueCountFrequency (%)
5221
 
5.2%
4121
 
5.2%
4819
 
4.8%
4419
 
4.8%
4016
 
4.0%
4314
 
3.5%
4213
 
3.2%
4513
 
3.2%
3612
 
3.0%
3312
 
3.0%
Other values (34)170
42.5%
(Missing)70
17.5%

Length

2022-04-11T13:41:40.281479image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

pe
Boolean

HIGH CORRELATION

Distinct2
Distinct (%)0.5%
Missing1
Missing (%)0.2%
Memory size928.0 B
False
323 
True
76 
(Missing)
 
1
ValueCountFrequency (%)
False323
80.8%
True76
 
19.0%
(Missing)1
 
0.2%
2022-04-11T13:41:40.463777image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

pot
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct40
Distinct (%)12.8%
Missing88
Missing (%)22.0%
Infinite0
Infinite (%)0.0%
Mean4.62724359
Minimum2.5
Maximum47
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2022-04-11T13:41:40.532470image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum2.5
5-th percentile3.4
Q13.8
median4.4
Q34.9
95-th percentile5.7
Maximum47
Range44.5
Interquartile range (IQR)1.1

Descriptive statistics

Standard deviation3.193904177
Coefficient of variation (CV)0.6902390407
Kurtosis142.5059115
Mean4.62724359
Median Absolute Deviation (MAD)0.5
Skewness11.58295556
Sum1443.7
Variance10.20102389
MonotonicityNot monotonic
2022-04-11T13:41:40.630560image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
3.530
 
7.5%
530
 
7.5%
4.927
 
6.8%
4.717
 
4.2%
4.816
 
4.0%
414
 
3.5%
4.114
 
3.5%
4.414
 
3.5%
3.914
 
3.5%
3.814
 
3.5%
Other values (30)122
30.5%
(Missing)88
22.0%
ValueCountFrequency (%)
2.52
 
0.5%
2.71
 
0.2%
2.81
 
0.2%
2.93
 
0.8%
32
 
0.5%
3.23
 
0.8%
3.33
 
0.8%
3.45
 
1.2%
3.530
7.5%
3.68
 
2.0%
ValueCountFrequency (%)
471
 
0.2%
391
 
0.2%
7.61
 
0.2%
6.61
 
0.2%
6.52
0.5%
6.41
 
0.2%
6.33
0.8%
5.92
0.5%
5.82
0.5%
5.74
1.0%

rbc
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct2
Distinct (%)0.8%
Missing152
Missing (%)38.0%
Memory size3.2 KiB
normal
201 
abnormal
47 

Length

Max length8
Median length6
Mean length6.379032258
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rownormal
2nd rownormal
3rd rownormal
4th rownormal
5th rownormal

Common Values

ValueCountFrequency (%)
normal201
50.2%
abnormal47
 
11.8%
(Missing)152
38.0%

Length

2022-04-11T13:41:40.754382image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-04-11T13:41:40.818012image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

rc
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct49
Distinct (%)18.1%
Missing130
Missing (%)32.5%
Memory size3.2 KiB
5.2
 
18
4.5
 
16
4.9
 
14
4.7
 
11
3.9
 
10
Other values (44)
201 

Length

Max length3
Median length3
Mean length2.951851852
Min length1

Unique

Unique5 ?
Unique (%)1.9%

Sample

1st row5.2
2nd row3.9
3rd row4.6
4th row4.4
5th row5

Common Values

ValueCountFrequency (%)
5.218
 
4.5%
4.516
 
4.0%
4.914
 
3.5%
4.711
 
2.8%
3.910
 
2.5%
4.810
 
2.5%
4.69
 
2.2%
3.49
 
2.2%
5.98
 
2.0%
5.58
 
2.0%
Other values (39)157
39.2%
(Missing)130
32.5%

Length

2022-04-11T13:41:40.879155image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

sc
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct84
Distinct (%)21.9%
Missing17
Missing (%)4.2%
Infinite0
Infinite (%)0.0%
Mean3.072454308
Minimum0.4
Maximum76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2022-04-11T13:41:40.992305image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0.4
5-th percentile0.5
Q10.9
median1.3
Q32.8
95-th percentile11.89
Maximum76
Range75.6
Interquartile range (IQR)1.9

Descriptive statistics

Standard deviation5.741126067
Coefficient of variation (CV)1.868579803
Kurtosis79.30434545
Mean3.072454308
Median Absolute Deviation (MAD)0.6
Skewness7.509538252
Sum1176.75
Variance32.96052852
MonotonicityNot monotonic
2022-04-11T13:41:41.114846image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.240
 
10.0%
1.124
 
6.0%
0.523
 
5.8%
123
 
5.8%
0.922
 
5.5%
0.722
 
5.5%
0.618
 
4.5%
0.817
 
4.2%
2.210
 
2.5%
1.59
 
2.2%
Other values (74)175
43.8%
(Missing)17
 
4.2%
ValueCountFrequency (%)
0.41
 
0.2%
0.523
5.8%
0.618
4.5%
0.722
5.5%
0.817
4.2%
0.922
5.5%
123
5.8%
1.124
6.0%
1.240
10.0%
1.38
 
2.0%
ValueCountFrequency (%)
761
0.2%
48.11
0.2%
321
0.2%
241
0.2%
18.11
0.2%
181
0.2%
16.91
0.2%
16.41
0.2%
15.21
0.2%
151
0.2%

sg
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct5
Distinct (%)1.4%
Missing47
Missing (%)11.8%
Infinite0
Infinite (%)0.0%
Mean1.017407932
Minimum1.005
Maximum1.025
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2022-04-11T13:41:41.229899image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum1.005
5-th percentile1.01
Q11.01
median1.02
Q31.02
95-th percentile1.025
Maximum1.025
Range0.02
Interquartile range (IQR)0.01

Descriptive statistics

Standard deviation0.005716616974
Coefficient of variation (CV)0.005618805196
Kurtosis-1.144356928
Mean1.017407932
Median Absolute Deviation (MAD)0.005
Skewness-0.1724437507
Sum359.145
Variance3.267970963 × 10-5
MonotonicityNot monotonic
2022-04-11T13:41:41.310877image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%)
1.02106
26.5%
1.0184
21.0%
1.02581
20.2%
1.01575
18.8%
1.0057
 
1.8%
(Missing)47
11.8%
ValueCountFrequency (%)
1.0057
 
1.8%
1.0184
21.0%
1.01575
18.8%
1.02106
26.5%
1.02581
20.2%
ValueCountFrequency (%)
1.02581
20.2%
1.02106
26.5%
1.01575
18.8%
1.0184
21.0%
1.0057
 
1.8%

sod
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct34
Distinct (%)10.9%
Missing87
Missing (%)21.8%
Infinite0
Infinite (%)0.0%
Mean137.528754
Minimum4.5
Maximum163
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2022-04-11T13:41:41.413795image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum4.5
5-th percentile125
Q1135
median138
Q3142
95-th percentile150
Maximum163
Range158.5
Interquartile range (IQR)7

Descriptive statistics

Standard deviation10.40875205
Coefficient of variation (CV)0.07568418785
Kurtosis85.53436962
Mean137.528754
Median Absolute Deviation (MAD)3
Skewness-6.996568561
Sum43046.5
Variance108.3421193
MonotonicityNot monotonic
2022-04-11T13:41:41.530021image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
13540
10.0%
14025
 
6.2%
14122
 
5.5%
13921
 
5.2%
14220
 
5.0%
13820
 
5.0%
13719
 
4.8%
15017
 
4.2%
13617
 
4.2%
14713
 
3.2%
Other values (24)99
24.8%
(Missing)87
21.8%
ValueCountFrequency (%)
4.51
 
0.2%
1041
 
0.2%
1111
 
0.2%
1132
0.5%
1142
0.5%
1151
 
0.2%
1202
0.5%
1222
0.5%
1243
0.8%
1252
0.5%
ValueCountFrequency (%)
1631
 
0.2%
15017
4.2%
14713
3.2%
14610
 
2.5%
14511
2.8%
1449
 
2.2%
1434
 
1.0%
14220
5.0%
14122
5.5%
14025
6.2%

su
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
ZEROS

Distinct6
Distinct (%)1.7%
Missing49
Missing (%)12.2%
Infinite0
Infinite (%)0.0%
Mean0.4501424501
Minimum0
Maximum5
Zeros290
Zeros (%)72.5%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2022-04-11T13:41:41.616611image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.099191252
Coefficient of variation (CV)2.441874237
Kurtosis5.055348003
Mean0.4501424501
Median Absolute Deviation (MAD)0
Skewness2.464261823
Sum158
Variance1.208221408
MonotonicityNot monotonic
2022-04-11T13:41:41.745562image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0290
72.5%
218
 
4.5%
314
 
3.5%
413
 
3.2%
113
 
3.2%
53
 
0.8%
(Missing)49
 
12.2%
ValueCountFrequency (%)
0290
72.5%
113
 
3.2%
218
 
4.5%
314
 
3.5%
413
 
3.2%
53
 
0.8%
ValueCountFrequency (%)
53
 
0.8%
413
 
3.2%
314
 
3.5%
218
 
4.5%
113
 
3.2%
0290
72.5%

wc
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct92
Distinct (%)31.2%
Missing105
Missing (%)26.2%
Memory size3.2 KiB
9800
 
11
6700
 
10
9600
 
9
7200
 
9
9200
 
9
Other values (87)
247 

Length

Max length5
Median length4
Mean length4.227118644
Min length2

Unique

Unique34 ?
Unique (%)11.5%

Sample

1st row7800
2nd row6000
3rd row7500
4th row6700
5th row7300

Common Values

ValueCountFrequency (%)
980011
 
2.8%
670010
 
2.5%
96009
 
2.2%
72009
 
2.2%
92009
 
2.2%
69008
 
2.0%
58008
 
2.0%
110008
 
2.0%
78007
 
1.8%
70007
 
1.8%
Other values (82)209
52.2%
(Missing)105
26.2%

Length

2022-04-11T13:41:41.811164image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

 

2022-04-11T12:09:52.587492image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:10:17.717076image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:11:06.009092image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:12:26.214167image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:14:31.692223image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:17:11.724084image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:22:35.114408image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:28:44.919165image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:36:29.838204image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:45:38.832806image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:56:23.639362image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T13:09:50.424943image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:09:54.028790image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:10:20.644407image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:11:11.460309image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:12:34.310289image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:14:43.190729image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:17:40.371948image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:23:02.964157image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:29:21.472679image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:37:04.516392image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:46:31.740777image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:57:29.133135image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T13:11:09.067750image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:09:55.527925image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:10:23.843390image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:11:16.992484image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:12:42.752826image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:14:55.022802image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:18:00.530081image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:23:40.623986image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:29:59.064958image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:37:40.054604image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:47:28.597717image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:58:31.206025image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T13:12:29.175690image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:09:57.155622image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:10:27.229293image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:11:22.810827image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:12:51.426650image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:15:07.080298image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:18:22.568910image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:24:05.918822image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:30:37.005685image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:38:15.546856image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:48:23.572176image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:59:39.177319image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T13:13:51.356310image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:09:58.998224image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:10:30.824401image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:11:28.811300image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:13:00.393102image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:15:19.619940image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:19:04.358862image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:24:26.859530image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:31:15.678531image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:38:57.028373image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:49:17.983905image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T13:00:48.068966image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T13:15:15.284706image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:10:00.805431image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:10:34.576172image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-04-11T12:11:34.977566image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
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